Ultrasound image display method and apparatus, storage medium, and electronic device

ABSTRACT

This present disclosure describes an ultrasound image display method and apparatus, a storage medium, and an electronic device. The method includes acquiring, by a device, an input signal by performing detection on a to-be-detected object, the input signal comprising a three-dimensional (3D) radio-frequency (RF) signal. The device includes a memory storing instructions and a processor in communication with the memory. The method also includes performing, by the device, a modulus calculation on the 3D RF signal to obtain envelope information in a 3D ultrasound image, the modulus calculation being at least used for directly acquiring a 3D amplitude of the 3D RF signal; and displaying, by the device, the envelope information in the 3D ultrasound image, the envelope information being at least used for indicating the to-be-detected object.

RELATED APPLICATION

This application is a continuation application of PCT Patent ApplicationNo. PCT/CN2019/082216, filed on Apr. 11, 2019, which claims priority toChinese Patent Application No. 201810508663.2, filed with the NationalIntellectual Property Administration, P.R. China on May 24, 2018, bothof which are incorporated herein by reference in their entireties.

FIELD OF THE TECHNOLOGY

This application relates to the field of computers, and specifically, todisplay of an ultrasound image.

BACKGROUND OF THE DISCLOSURE

Envelope detection is an important step of reconstruction of abrightness-mode ultrasound image (B-mode ultrasound image). A basicprocess of the reconstruction of the B-mode ultrasound image includes:acquiring a high-frequency radio frequency (RF) signal from anultrasound probe, the original RF signal being a one-dimensional signalalong a direction of the ultrasound probe; then performing the Hilberttransform on the one-dimensional signal to construct a one-dimensionalanalytic signal, an amplitude value of the one-dimensional analyticsignal calculated being a one-dimensional envelope signal; and splicinga plurality of one-dimensional envelope signals into a two-dimensionalsignal according to a location of the probe, to acquire atwo-dimensional envelope image and acquire a two-dimensional B-modeultrasound image after some post-processing. At present, athree-dimensional (3D) B-mode ultrasound image is mostly acquired aftersome post-processing is performed a 3D envelope image that is obtainedthrough splicing based on one-dimensional envelope signals.

SUMMARY

Embodiments of this application provide an ultrasound image displaymethod and apparatus, a storage medium and an electronic device, toimprove the accuracy of a three-dimensional (3D) B-mode ultrasoundimage.

The present disclosure describes a method for displaying an ultrasoundimage. The method includes acquiring, by a device, an input signal byperforming detection on a to-be-detected object, the input signalcomprising a three-dimensional (3D) radio-frequency (RF) signal. Thedevice includes a memory storing instructions and a processor incommunication with the memory. The method also includes performing, bythe device, a modulus calculation on the 3D RF signal to obtain envelopeinformation in a 3D ultrasound image, the modulus calculation being atleast used for directly acquiring a 3D amplitude of the 3D RF signal;and displaying, by the device, the envelope information in the 3Dultrasound image, the envelope information being at least used forindicating the to-be-detected object.

The present disclosure describes an apparatus for displaying anultrasound image. The apparatus includes a memory storing instructions;and a processor in communication with the memory. When the processorexecutes the instructions, the processor is configured to cause theapparatus to acquire an input signal by performing detection on ato-be-detected object, the input signal comprising a three-dimensional(3D) radio-frequency (RF) signal, perform a modulus calculation on the3D RF signal to obtain envelope information in a 3D ultrasound image,the modulus calculation being at least used for directly acquiring a 3Damplitude of the 3D RF signal, and display the envelope information inthe 3D ultrasound image, the envelope information being at least usedfor indicating the to-be-detected object.

The present disclosure describes a non-transitory computer readablestorage medium storing computer readable instructions. The computerreadable instructions, when executed by a processor, are configured tocause the processor to perform acquiring an input signal by performingdetection on a to-be-detected object, the input signal comprising athree-dimensional (3D) radio-frequency (RF) signal; performing a moduluscalculation on the 3D RF signal to obtain envelope information in a 3Dultrasound image, the modulus calculation being at least used fordirectly acquiring a 3D amplitude of the 3D RF signal; and displayingthe envelope information in the 3D ultrasound image, the envelopeinformation being at least used for indicating the to-be-detectedobject.

According to another aspect of the embodiments of this application, anelectronic device is further provided, including a memory and aprocessor, the memory storing a computer program, and the processorbeing configured to perform any ultrasound image display method in theembodiments of this application through the computer program.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings described herein are used for providing afurther understanding of this application, and form a part of thisapplication. Exemplary embodiments of this application and descriptionsthereof are used for explaining this application, and do not constituteany inappropriate limitation to this application. In the accompanyingdrawings:

FIG. 1 is a schematic diagram of a hardware environment of an ultrasoundimage display method according to an embodiment of this application.

FIG. 2 is a flowchart of an optional ultrasound image display methodaccording to an embodiment of this application.

FIG. 3 is a schematic diagram of forming a plane by splicing envelopesof one-dimensional signals in the related art.

FIG. 4 is a schematic diagram of 8 orthants in a 3D frequency domainaccording to an embodiment of this application.

FIG. 5 is a schematic diagram of a platform where a three-dimensional(3D) radio-frequency (RF) signal is collected according to an embodimentof this application.

FIG. 6 is a structural diagram of a 3D RF signal according to anembodiment of this application.

FIG. 7 is a comparison diagram of an envelope image in a 3D ultrasoundimage according to an embodiment of this application.

FIG. 8 is an enlarged schematic diagram of an envelope image in a 3Dultrasound image according to an embodiment of this application.

FIG. 9 is an enlarged schematic diagram of a brightness comparison inthe vertical direction according to an embodiment of this application.

FIG. 10 is an enlarged schematic diagram of a brightness comparison inthe biopsy needle direction according to an embodiment of thisapplication.

FIG. 11 is a schematic diagram of a platform where a 3D RF signal iscollected by a linear probe according to an embodiment of thisapplication.

FIG. 12 is a structural diagram of a 3D RF signal collected by a linearprobe according to an embodiment of this application.

FIG. 13 is a comparison diagram of an envelope image in a 3D ultrasoundimage collected by a linear probe according to an embodiment of thisapplication.

FIG. 14 is a schematic diagram of a brightness comparison of an envelopeimage in the vertical direction in a 3D ultrasound image collected by alinear probe according to an embodiment of this application.

FIG. 15 is a schematic diagram of a brightness comparison of an envelopeimage in the biopsy needle direction in a 3D ultrasound image collectedby a linear probe according to an embodiment of this application.

FIG. 16 is a schematic diagram of an optional ultrasound image displayapparatus according to an embodiment of this application.

FIG. 17 is a structural block diagram of an electronic device accordingto an embodiment of this application.

DESCRIPTION OF EMBODIMENTS

To make solutions of this application more comprehensible for a personskilled in the art, the following clearly and completely describes thetechnical solutions in the embodiments of this application withreference to the accompanying drawings in the embodiments of thisapplication. Apparently, the described embodiments are merely a partrather than all of the embodiments of this application. All otherembodiments obtained by a person of ordinary skill in the art based onthe embodiments of this application without creative efforts shall fallwithin the protection scope of this application.

The terms such as “first” and “second” in the specification, claims, andaccompanying drawings of this application are intended to distinguishbetween similar objects rather than describe a particular sequence or achronological order. It is to be understood that the data termed in sucha way are interchangeable in proper circumstances so that theembodiments of this application described herein can be implemented inorders except the order illustrated or described herein. In addition,the terms “include”, “comprise” and any other variants are intended tocover the non-exclusive inclusion. For example, a process, method,system, product, or device that includes a series of steps or units isnot necessarily limited to those expressly listed steps or units, butmay include other steps or units not expressly listed or inherent tosuch a process, method, product, or device.

Throughout the specification and claims, terms may have nuanced meaningssuggested or implied in context beyond an explicitly stated meaning.Likewise, the phrase “in one embodiment” or “in one implementation” asused herein does not necessarily refer to the same embodiment orimplementation and the phrase “in another embodiment” or “in anotherimplementation” as used herein does not necessarily refer to a differentembodiment or implementation. It is intended, for example, that claimedsubject matter includes combinations of exemplary embodiments orimplementations in whole or in part.

In general, terminology may be understood at least in part from usage incontext. For example, terms, such as “and”, “or”, or “and/or,” as usedherein may include a variety of meanings that may depend at least inpart upon the context in which such terms are used. Typically, “or” ifused to associate a list, such as A, B or C, is intended to mean A, B,and C, here used in the inclusive sense, as well as A, B or C, here usedin the exclusive sense. In addition, the term “one or more” or “at leastone” as used herein, depending at least in part upon context, may beused to describe any feature, structure, or characteristic in a singularsense or may be used to describe combinations of features, structures orcharacteristics in a plural sense. Similarly, terms, such as “a”, “an”,or “the”, again, may be understood to convey a singular usage or toconvey a plural usage, depending at least in part upon context. Inaddition, the term “based on” or “determined by” may be understood asnot necessarily intended to convey an exclusive set of factors and may,instead, allow for existence of additional factors not necessarilyexpressly described, again, depending at least in part on context.

According to an aspect of the embodiments of this application, anultrasound image display method is provided.

Optionally, in this embodiment, the ultrasound image display method maybe applied to a hardware environment composed of a server 102 and adetection device 104 shown in FIG. 1. As shown in FIG. 1, the server 102is connected to the detection device 104 by a network 110. The network110 includes, but is not limited to, a wide area network, a metropolitanarea network or a local area network. The detection device 104 mayinclude, but is not limited to, an ultrasound device.

Optionally, the ultrasound image display method in this embodiment ofthis application may be performed by the detection device 104 and adisplay device together. The specific execution process may be describedas: acquiring, by the detection device, an input signal obtained byperforming detection on a to-be-detected object by the detection device,the input signal being a three-dimensional (3D) radio-frequency (RF)signal; performing a one-time modulus value calculation on the 3D RFsignal to obtain envelope information in a 3D ultrasound image, theone-time modulus value calculation being at least used for directlyacquiring a 3D amplitude of the 3D RF signal; generating, by thedetection device, the 3D ultrasound image according to the envelopeinformation and sending the 3D ultrasound image to the display device;and displaying the envelope information in the 3D ultrasound image onthe display device, the envelope information being used for indicatingthe to-be-detected object.

Optionally, the detection device and the display device may form anintegral structure. For example, the detection device 104 shown in FIG.1 is the integral structure composed of the detection device and thedisplay device. Alternatively, the detection device and the displaydevice may be separate components. The detection device is configured togenerate the 3D ultrasound image and the display device is configured todisplay the 3D ultrasound image.

The following provides a detailed description about the ultrasound imagedisplay method in this embodiment of this application.

FIG. 2 is a flowchart of an optional ultrasound image display methodaccording to an embodiment of this application. As shown in FIG. 2, themethod may include the following steps:

S202. Acquire an input signal obtained by performing detection on ato-be-detected object, the input signal comprising a three-dimensional(3D) radio-frequency (RF) signal.

S204. Perform a modulus calculation on the 3D RF signal to obtainenvelope information in a 3D ultrasound image, the modulus calculationbeing at least used for directly acquiring a 3D amplitude of the 3D RFsignal.

In one implementation, the modulus calculation on the 3D RF signal mayinclude a one-time modulus value calculation on the 3D RF signal toobtain the envelope information in the 3D ultrasound image.

S206. Display the envelope information in the 3D ultrasound image, theenvelope information being at least used for indicating theto-be-detected object.

Through the foregoing S202 to S206, by acquiring the input signalobtained by performing the detection on the to-be-detected object by thedetection device, the input signal being the 3D RF signal; performingthe modulus calculation on the 3D RF signal to obtain the envelopeinformation in the 3D ultrasound image, the modulus calculation being atleast used for directly acquiring the 3D amplitude of the 3D RF signal;and displaying the envelope information in the 3D ultrasound image onthe display device, the envelope information being used for indicatingthe to-be-detected object, the to-be-detected object is accuratelydisplayed in the 3D ultrasound image, to achieve a technical effect ofimproving the accuracy of the 3D ultrasound image, thereby solving thetechnical problem that the 3D B-mode ultrasound image reconstructed inthe related art has a reconstruction error that reduces the accuracy ofthe 3D B-mode ultrasound image.

In the technical solution provided in S202, the detection device mayinclude, but is not limited to, an ultrasound device. The detectiondevice may be configured to detect the to-be-detected object, a type ofthe to-be-detected object being not specifically limited in thisembodiment of this application. For example, the to-be-detected objectmay be a human organ (for example, the kidney or the liver). When thedetection device detects the to-be-detected object, the detection devicemay send a detection signal. A signal obtained after the detectionsignal is reflected by the to-be-detected object is an input signal,where the input signal may be a real signal and/or the input signal maybe a high-frequency 3D RF signal.

In the technical solution provided in S204, after the input signal isacquired, in this embodiment of this application, the moduluscalculation may be performed on the input signal, that is, the moduluscalculation is performed on the 3D RF signal, to obtain the envelopeinformation in the 3D ultrasound image, where the envelope informationin the 3D ultrasound image may be used for indicating the to-be-detectedobject. The modulus calculation may at least be used for directlyacquiring the 3D amplitude of the 3D RF signal, where the envelopeinformation may include the 3D amplitude of the 3D RF signal. In thisembodiment of this application, by performing the modulus calculation onthe 3D RF signal, the envelope information in the 3D ultrasound image isobtained. Compared with obtaining the 3D ultrasound image by splicingone-dimensional envelope information, this embodiment of thisapplication may make the brightness of the to-be-detected objectindicated by the envelope information in the 3D ultrasound image begreater than the brightness of the to-be-detected object in aone-dimensional ultrasound image or a two-dimensional ultrasound image,to clearly display the to-be-detected object in the 3D ultrasound image,thereby improving the accuracy of the 3D ultrasound image.

The following provides a detailed description about a specific processof performing the modulus calculation on the 3D RF signal to obtain theenvelope information in the 3D ultrasound image:

Optionally, S204 of performing the modulus calculation on the 3D RFsignal may include the following S2042 and S2044:

S2042. Acquire a first hypercomplex signal corresponding to the 3D RFsignal, the first hypercomplex signal being a sum of 8 components, andeach component being represented by modulus values and angles of aplurality of analytic signals corresponding to the input signal.

S2044. Acquire a modulus value of the first hypercomplex signal, themodulus value of the first hypercomplex signal being used forrepresenting the 3D amplitude of the 3D RF signal, and envelopeinformation including the modulus value of the first hypercomplexsignal.

For S2042, optionally, the acquiring the first hypercomplex signalcorresponding to the input signal may include: acquiring a secondhypercomplex signal corresponding to the input signal, the secondhypercomplex signal including 8 components, and each component beingrepresented by the Hilbert transform of the input signal; acquiring acorrespondence between the components represented by the Hilberttransform and the modulus values and angles of the plurality of analyticsignals; and transforming the second hypercomplex signal into the firsthypercomplex signal according to the correspondence.

Optionally, the input signal of the 3D RF signal may be defined as f(x,y, z) herein, and a hypercomplex signal ψ_(cas) (x, y, z) of f(x, y, z)is defined as formula (3):

$\begin{matrix}{{\psi_{cas}\left( {x,y,z} \right)} = {{f\left( {x,y,z} \right)}{\bigstar\bigstar\bigstar}{\left\{ {{\left\lbrack {{\delta (x)} + \frac{e_{1}}{\pi \; x}} \right\rbrack \left\lbrack {{\delta (y)} + \frac{e_{2}}{\pi \; y}} \right\rbrack}\left\lbrack {{\delta (z)} + \frac{e_{3}}{\pi \; z}} \right\rbrack} \right\}.}}} & (3)\end{matrix}$

The hypercomplex signal ψ_(cas)(x, y, z) uses 3 bases of complex units:e₁, e₂, and e₃, to define an imaginary unit. The theoretical foundationthereof is derived from the definition of a biquaternion. The followingexplains related contents:

When it is defined that e₁=e₂=e₃=i, they are a conventional imaginaryunit i shown in formula (1).

Conventional one-dimensional envelope detection is implemented by usinga one-dimensional analytic signal. For a one-dimensional RF signal f(x),the one-dimensional Hilbert transform H{(f(x)}, and they arerespectively used as a real part and an imaginary part to form a complexsignal, that is, the one-dimensional analytic signal f_(A)(x), as shownin formula (1):

f _(A)(x)=f(x)+iH{f(x)},x∈

  (1)

i is the complex unit and x belongs to a real number R. An amplitudevalue of the one-dimensional high-frequency signal is shown in formula(2):

|f _(A)(x)|=√{square root over (f(x)²+(H{f(x)})²)}  (2)

When e1, e2, and e3 are different from each other, they can generate 8different imaginary units (2³=8). The definition is shown in formula(4):

[1,i=c ₂ c ₃ ,j=e ₃ e ₁ ,k=e ₁ e ₂ ,ϵ=−e ₁ e ₂ e ₃ ,ϵi=e ₁ ,ϵj=e ₂ ,ϵk=e₃]  (4)

where 1 represents the real part, ϵ²=1, and e₁ ²=e₂ ²=e₃ ²=−1.

In formula (3), *** represents a 3D convolution calculation. δ(x), δ(y),and δ(z) are Dirac delta functions. For the 3D RF signal, the x axis,the y axis and the z axis herein may respectively correspond to physicalinterpretations of the x axis, the y axis and the z axis in FIG. 3. FIG.3 is a schematic diagram of sending a RF signal by a 3D ultrasoundfan-shaped probe. The high-frequency signal f(x) represents aone-dimensional RF signal sent by the ultrasound probe. A plurality ofone-dimensional RF signals form one plane and a plurality of planes formone piece of 3D RF volume data.

Formula (3) is further spread out and calculated to obtain formula (5):

$\begin{matrix}{{{\psi_{cas}\left( {x,y,z} \right)} = {{{f\left( {x,y,z} \right)}{\bigstar\bigstar\bigstar}\left\{ {{\left\lbrack {{\delta (x)} + \frac{e_{1}}{\pi \; x}} \right\rbrack \left\lbrack {{\delta (y)} + \frac{e_{2}}{\pi \; y}} \right\rbrack}\left\lbrack {{\delta (z)} + \frac{e_{3}}{\pi \; z}} \right\rbrack} \right\}} = {{f\left( {x,y,z} \right)}{\bigstar\bigstar\bigstar}\left\{ {{{\delta (x)}{\delta (y)}{\delta (z)}} + {{\delta (x)}{\delta (y)}\frac{e_{3}}{\pi \; z}} + {{\delta (x)}\frac{e_{2}}{\pi \; y}{\delta (z)}} + {{\delta (x)}\frac{e_{2}}{\pi \; y}\frac{e_{3}}{\pi \; z}} + {\frac{e_{1}}{\pi \; x}\delta (y){\delta (z)}} + {\frac{e_{1}}{\pi \; x}{\delta (y)}\frac{e_{3}}{\pi \; z}} + {\frac{e_{1}}{\pi \; x}\frac{e_{2}}{\pi \; y}{\delta (z)}} + {\frac{e_{1}}{\pi \; x}\frac{e_{2}}{\pi \; y}\frac{e_{3}}{\pi \; z}}} \right\}}}},} & (5)\end{matrix}$

The convolution calculation in formula (5) is spread out, and thefollowing 8 convolution calculations may be seen (see formula (6)). Inaddition, according to formula (4), an imaginary unit of eachconvolution in formula (6) may be calculated, as shown in formula (6):

$\begin{matrix}{\mspace{79mu} {{{{f\left( {x,y,z} \right)}{{\bigstar\bigstar\bigstar}\left\lbrack {{\delta (x)}{\delta (y)}{\delta (z)}} \right\rbrack}} = {f\left( {x,y,z} \right)}},\mspace{20mu} {{{f\left( {x,y,z} \right)}{{\bigstar\bigstar\bigstar}\left\lbrack {{\delta (x)}{\delta (y)}\frac{e_{3}}{\pi \; z}} \right\rbrack}} = {{e_{3}H_{z}\left\{ f \right\}} = {\epsilon \; {kH}_{z}\left\{ f \right\}}}},\mspace{20mu} {{{f\left( {x,y,z} \right)}{{\bigstar\bigstar\bigstar}\left\lbrack {{\delta (x)}\frac{e_{2}}{\pi \; y}{\delta (z)}} \right\rbrack}} = {{e_{2}H_{y}\left\{ f \right\}} = {\epsilon \; {jH}_{y}\left\{ f \right\}}}},\mspace{20mu} {{{f\left( {x,y,z} \right)}{{\bigstar\bigstar\bigstar}\left\lbrack {\frac{e_{1}}{\pi \; x}{\delta (y)}{\delta (z)}} \right\rbrack}} = {{e_{1}H_{x}\left\{ f \right\}} = {\epsilon \; {iH}_{x}\left\{ f \right\}}}},\mspace{20mu} {{{f\left( {x,y,z} \right)}{{\bigstar\bigstar\bigstar}\left\lbrack {{\delta (x)}\frac{e_{2}}{\pi \; y}\frac{e_{3}}{\pi \; z}} \right\rbrack}} = {{e_{2}e_{3}H_{yz}\left\{ f \right\}} = {{iH}_{yz}\left\{ f \right\}}}},{{{f\left( {x,y,z} \right)}{{\bigstar\bigstar\bigstar}\left\lbrack {\frac{e_{1}}{\pi \; x}{\delta (y)}\frac{e_{3}}{\pi \; z}} \right\rbrack}} = {{e_{1}e_{3}H_{xz}\left\{ f \right\}} = {{{- e_{3}}e_{1}H_{xz}\left\{ f \right\}} = {{- {jH}_{xz}}\left\{ f \right\}}}}},\mspace{20mu} {{{f\left( {x,y,z} \right)}{{\bigstar\bigstar\bigstar}\left\lbrack {\frac{e_{1}}{\pi \; x}\frac{e_{2}}{\pi \; y}{\delta (z)}} \right\rbrack}} = {{e_{1}e_{2}H_{xy}\left\{ f \right\}} = {{kH}_{xy}\left\{ f \right\}}}},\mspace{20mu} {{{f\left( {x,y,z} \right)}{{\bigstar\bigstar\bigstar}\left\lbrack {\frac{e_{1}}{\pi \; x}\frac{e_{2}}{\pi \; y}\frac{e_{3}}{\pi \; z}} \right\rbrack}} = {{e_{1}e_{2}e_{3}H\left\{ f \right\}} = {{- \epsilon}\; H{\left\{ f \right\}.}}}}}} & (6)\end{matrix}$

In formula (6), H{f} represents the Hilbert transform of signal f(x, y,z). H_(z){f} represents the Hilbert transform of signal f(x, y, z) inthe z direction, H_(y){f} represents the Hilbert transform of signalf(x, y, z) in the y direction, H_(x){f} represents the Hilbert transformof signal f(x, y, z) in the x direction, H_(yz){f} represents theHilbert transform of signal f(x, y, z) in the y direction and the zdirection, H_(xz){f} represents the Hilbert transform of signal f(x, y,z) in the x direction and the z direction, and H_(xy){f} represents theHilbert transform of signal f(x, y, z) in the x direction and the ydirection.

If a result of formula (6) is substituted into formula (5), ahypercomplex signal ψ_(cas) (x, y, z) may be written as shown in formula(7):

$\begin{matrix}{{\psi_{cas}\left( {x,y,z} \right)} = {f + {{iH}_{yz}\left\{ f \right\}} + {j\left( {{- H_{xz}}\left\{ f \right\}} \right)} + {{kH}_{xy}\left\{ f \right\}} + {\epsilon \left( {{- H}\left\{ f \right\}} \right)} + {\epsilon \; {iH}_{x}\left\{ f \right\}} + {\epsilon \; {jH}_{y}\left\{ f \right\}} + {\epsilon \; {kH}_{z}\left\{ f \right\}}}} & (7)\end{matrix}$

The hypercomplex signal in formula (7) is the second hypercomplex signalin this embodiment of this application.

In conclusion, the second hypercomplex signal corresponding to the inputsignal f(x, y, z) of the 3D RF signal is shown in formula (7). Eachcomponent of the hypercomplex signal is represented by the Hilberttransform of the input signal.

Formula (7) is a theoretical value. Next, each component needs to becalculated from the perspective of engineering, and then the amplitudevalue (theoretical value) of the hypercomplex signal is calculated,thereby acquiring the amplitude value (theoretical value) of thehypercomplex signal from the perspective of engineering.

The foregoing content defines the hypercomplex signal in a form ofconvolution, and defines the imaginary unit of the hypercomplex signalby using three bases of the biquaternion. The beneficial effect is thatthe form of definition is a macroscopic form of a conventional complexnumber and a quaternion, and may process 3D data and express theconventional complex number (one real part and one imaginary part) andthe quaternion (one real part and three imaginary parts) in a downwardcompatible manner.

A method for indirectly calculating the Hilbert transform in eachcomponent of the hypercomplex signal is needed to acquire a mathematicalexpression, of a result of formula (7), that can be implemented inengineering.

Because it is very difficult to directly calculate the Hilbert transformtheoretically, a method for indirectly calculating the Hilbert transformis described herein. The method may be implemented in engineering butnot in a theoretical formula.

Engineering implementation means that: it may be implemented by using acommon programming language and an open code library.

For the input signal f(x, y, z) of the 3D RF signal, a calculatedsingle-orthant analytic signal of f(x, y, z) is a signal obtained byperforming inverse Fourier transform on a single orthant of a 3D Fourierspectrum of a real signal f(x, y, z). The signal may be calculated byusing a Fourier transform function of a general programming language.

One 3D real signal is first transformed from a 3D real number domain toa 3D frequency domain through the Fourier transform. There are 8orthants in the 3D frequency domain, as shown in FIG. 4. In the 3Dfrequency domain, half of the spectrum includes all information aboutthe whole original signal. Therefore, in the 8 orthants of the 3Dfrequency domain, four adjacent orthants may be selected to include allinformation about the input signal. FIG. 4 shows the eight orthants inthe 3D frequency domain. It can be seen that, orthant I, orthant III,orthant V, and orthant VII are four adjacent orthants.

The eight orthants in the 3D frequency domain are in FIG. 4, where u, v,and w are 3 dimensions of the frequency domain.

The following describes a calculation process of four single-orthantanalytic signals, as shown in formula (8) to formula (11):

$\begin{matrix}{{{\psi_{1}\left( {x,y,z} \right)} = {{{f\left( {x,y,z} \right)}{\bigstar\bigstar\bigstar}\left\{ {{\left\lbrack {{\delta (x)} + \frac{i}{\pi \; x}} \right\rbrack \left\lbrack {{\delta (y)} + \frac{i}{\pi \; y}} \right\rbrack}\left\lbrack {{\delta (z)} + \frac{i}{\pi \; z}} \right\rbrack} \right\}} = {{\left( {f - {H_{xy}\left\{ f \right\}} - {H_{xz}\left\{ f \right\}} - {H_{yz}\left\{ f \right\}}} \right) + {i\left( {{H_{x}\left\{ f \right\}} + {H_{y}\left\{ f \right\}} + {H_{z}\left\{ f \right\}} - {H\left\{ f \right\}}} \right)}} = {{a_{1}e^{i\; \phi_{1}}} = {{a_{1}\cos \; \phi_{1}} + {i\; a_{1}\sin \; \phi_{1}}}}}}},} & (8) \\{{{\psi_{3}\left( {x,y,z} \right)} = {{{f\left( {x,y,z} \right)}{\bigstar\bigstar\bigstar}\left\{ {{\left\lbrack {{\delta (x)} + \frac{i}{\pi \; x}} \right\rbrack \left\lbrack {{\delta (y)} - \frac{i}{\pi \; y}} \right\rbrack}\left\lbrack {{\delta (z)} + \frac{i}{\pi \; z}} \right\rbrack} \right\}} = {{\left( {f + {H_{xy}\left\{ f \right\}} - {H_{xz}\left\{ f \right\}} + {H_{yz}\left\{ f \right\}}} \right) + {i\left( {{H_{x}\left\{ f \right\}} - {H_{y}\left\{ f \right\}} + {H_{z}\left\{ f \right\}} + {H\left\{ f \right\}}} \right)}} = {{a_{3}e^{i\; \phi_{3}}} = {{a_{3}\cos \; \phi_{3}} + {i\; a_{3}\sin \; \phi_{3}}}}}}},} & (9) \\{{{\psi_{5}\left( {x,y,z} \right)} = {{{f\left( {x,y,z} \right)}{\bigstar\bigstar\bigstar}\left\{ {{\left\lbrack {{\delta (x)} + \frac{i}{\pi \; x}} \right\rbrack \left\lbrack {{\delta (y)} + \frac{i}{\pi \; y}} \right\rbrack}\left\lbrack {{\delta (z)} - \frac{i}{\pi \; z}} \right\rbrack} \right\}} = {{\left( {f - {H_{xy}\left\{ f \right\}} + {H_{xz}\left\{ f \right\}} + {H_{yz}\left\{ f \right\}}} \right) + {i\left( {{H_{x}\left\{ f \right\}} + {H_{y}\left\{ f \right\}} - {H_{z}\left\{ f \right\}} + {H\left\{ f \right\}}} \right)}} = {{a_{5}e^{i\; \phi_{5}}} = {{a_{5}\cos \; \phi_{5}} + {i\; a_{5}\sin \; \phi_{5}}}}}}},} & (10) \\{{\psi_{7}\left( {x,y,z} \right)} = {{{f\left( {x,y,z} \right)}{\bigstar\bigstar\bigstar}\left\{ {{\left\lbrack {{\delta (x)} + \frac{i}{\pi \; x}} \right\rbrack \left\lbrack {{\delta (y)} - \frac{i}{\pi \; y}} \right\rbrack}\left\lbrack {{\delta (z)} - \frac{i}{\pi \; z}} \right\rbrack} \right\}} = {{\left( {f + {H_{xy}\left\{ f \right\}} + {H_{xz}\left\{ f \right\}} - {H_{yz}\left\{ f \right\}}} \right) + {i\left( {{H_{x}\left\{ f \right\}} - {H_{y}\left\{ f \right\}} - {H_{z}\left\{ f \right\}} - {H\left\{ f \right\}}} \right)}} = {{a_{7}e^{i\; \phi_{7}}} = {{a_{7}\cos \; \phi_{7}} + {i\; a_{7}\sin \; {\phi_{7}.}}}}}}} & (11)\end{matrix}$

ψ₁(x, y, z), ψ₃(x, y, z), ψ₅(x, y, z), and ω₇(x, y, z) representsingle-orthant analytic signals respectively acquired from orthant I,orthant III, orthant V, and orthant VII of the frequency domain in FIG.4. The difference between the signal and the definition in formula (3)is that: the definition uses the unique imaginary unit i, that is themost conventional definition of the complex number (a complex numberincluding one real part and one imaginary part). Similar to thecalculation method of formula (6), a 3D convolution of formula (8) toformula (11) has 8 components. The 8 components may each be representedby the Hilbert transform of the input signal f(x, y, z), which form realparts and imaginary parts of the single-orthant analytic signals.

Further, the foregoing formulas also define modulus values and angles ofthe single-orthant analytic signals (that is, a form of polarcoordinates of a complex number ψ₁(x, y, z)). For example, in formula(8), α₁(x, y, z) represents the modulus value in the form of the polarcoordinates of the complex number ψ₁(x, y, z) (α₁ herein may also bereferred to as an amplitude value). In formula (8), α₁(x, y, z) isshortened to α₁. φ₁(x, y, z) represents the angle in the form of thepolar coordinates of the complex number ψ₁(x, y, z) (φ₁ may also bereferred to as the phase herein). Similarly, in formula (8), φ₁(x, y, z)is shortened to φ₁. A specific calculation method thereof is shown informula (12):

$\begin{matrix}{{a_{1} = \sqrt{\begin{matrix}{\left( {f - {H_{xy}\left\{ f \right\}} - {H_{xz}\left\{ f \right\}} - {H_{yz}\left\{ f \right\}}} \right)^{2} +} \\\left( {{H_{x}\left\{ f \right\}} + {H_{y}\left\{ f \right\}} + {H_{z}\left\{ f \right\}} - {H\left\{ f \right\}}} \right)^{2}\end{matrix}}}{\phi_{1} = {\arctan \left( \frac{{H_{x}\left\{ f \right\}} + {H_{y}\left\{ f \right\}} + {H_{z}\left\{ f \right\}} - {H\left\{ f \right\}}}{f - {H_{xy}\left\{ f \right\}} - {H_{xz}\left\{ f \right\}} - {H_{yz}\left\{ f \right\}}} \right)}}} & (12)\end{matrix}$

The relationship between the modulus value α₁, the angle φ₁ and theHilbert transform may be obtained by formula (8), as shown in formula(13):

α₁ cos φ₁ =f−H _(xy) {f}−H _(xz) {f}−H _(yz) {f}

α₁ sin φ₁ =H _(x) {f}+H _(y) {f}+H _(z) {f}−H{f}  (13)

Similarly, the correspondence between the modulus values, the angles andthe Hilbert transform of the other three single-orthant analytic signalsmay be obtained from formula (9) to formula (11), as shown in formula(14):

f=¼(α₁ cos φ₁+α₃ cos φ₃+α₅ cos φ₅+α₇ cos φ₇),

H _(yz) {f}=¼(−α₁ cos φ₁+α₃ cos φ₃+α₅ cos φ₅−α₇ cos φ₇),

−H _(xz) {f}=¼(α₁ cos φ₁+α₃ cos φ₃−α₅ cos φ₅−α₇ cos φ₇),

H _(xy) {f}=¼(−α₁ cos φ₁+α₃ cos φ₃−α₅ cos φ₅+α₇ cos φ₇),

−H{f}=¼(α₁ sin φ₁−α₃ sin φ₃−α₅ sin φ₅+α₇ sin φ₇),

H _(x) {f}=¼(α₁ sin φ₁+α₃ sin φ₃+α₅ sin φ₅+α₇ sin φ₇),

H _(y) {f}=¼(α₁ sin φ₁−α₃ sin φ₃+α₅ sin φ₅−α₇ sin φ₇),

H _(z) {f}=¼(α₁ sin φ₁+α₃ sin φ₃−α₅ sin φ₅−α₇ sin φ₇),  (14)

Formula (14) may be used for representing a correspondence between thecomponents represented by the Hilbert transform and the modulus valueand angle of the analytic signal in this embodiment of this application.

Formula (14) uses the modulus value and angle of the analytic signal ofthe input signal to represent the Hilbert transform. It is relativelydifficult to obtain, through a calculation, the left part of formula(14) in engineering, while the right part of formula (14) may beobtained through a calculation of a library function of the Fouriertransform of the conventional programming language.

By substituting the result of formula (14) into formula (7), thehypercomplex signal ψ_(cas)(x, y, z) defined in mathematical theory iscalculated by the library function of the Fourier transform of theconventional programming language, which is the expression shown informula (15):

$\begin{matrix}{\psi_{cas} = {{\frac{1}{4}\left\lbrack {\left( {{a_{1}\cos \; \phi_{1}} + {a_{3}\cos \; \phi_{3}} + {a_{5}\cos \; \phi_{5}} + {a_{7}\cos \; \phi_{7}}} \right) + {i\left( {{{- a_{1}}\cos \; \phi_{1}} + {a_{3}\cos \; \phi_{3}} + {a_{5}\cos \; \phi_{5}} - {a_{7}\cos \; \phi_{7}}} \right)} + {j\left( {{a_{1}\cos \; \phi_{1}} + {a_{3}\cos \; \phi_{3}} - {a_{5}\cos \; \phi_{5}} - {a_{7}\cos \; \phi_{7}}} \right)} + {k\left( {{{- a_{1}}\cos \; \phi_{1}} + {a_{3}\cos \; \phi_{3}} - {a_{5}\cos \; \phi_{5}} + {a_{7}\cos \; \phi_{7}}} \right)} + {\epsilon \left( {{a_{1}\sin \; \phi_{1}} - {a_{3}\sin \; \phi_{3}} - {a_{5}\sin \; \phi_{5}} + \; {a_{7}\sin \; \phi_{7}}} \right)} + {\epsilon \; {i\left( {{a_{1}\sin \; \phi_{1}} + {a_{3}\sin \; \phi_{3}} + {a_{5}\sin \; \phi_{5}} + \; {a_{7}\sin \; \phi_{7}}} \right)}} + {\epsilon \; {j\left( {{a_{1}\sin \; \phi_{1}} - {a_{3}\sin \; \phi_{3}} + {a_{5}\sin \; \phi_{5}} - \; {a_{7}\sin \; \phi_{7}}} \right)}} + {\epsilon \; {k\left( {{a_{1}\sin \; \phi_{1}} + {a_{3}\sin \; \phi_{3}} - {a_{5}\sin \; \phi_{5}} - \; {a_{7}\sin \; \phi_{7}}} \right)}}} \right\rbrack}.}} & (15)\end{matrix}$

The hypercomplex signal in formula (15) is the first hypercomplex signalin this embodiment of this application.

In conclusion, the foregoing content theoretically converts the contentof the hypercomplex signal ψ_(cas)(x, y, z) into an expression inanother form, aiming to acquire an expression of the hypercomplex signalψ_(cas)(x, y, z) that can be implemented in engineering, as shown informula (15).

After acquiring the first hypercomplex signal shown in formula (15), themodulus value of the first hypercomplex signal may be calculated. Thespecific process of calculating the modulus value |ψ_(cas)(x, y, z)| ofthe hypercomplex signal may be described as follows:

Properties of several biquaternions need to be used when the modulusvalue is calculated:

Biquaternion property 1: multiplication of the biquaternion;

for a biquaternion A, the expression thereof may be shown in formula(16):

$\begin{matrix}\begin{matrix}{A = {p + {\epsilon \; q}}} \\{= {\left( {p_{0} + {ip}_{1} + {jp}_{2} + {kp}_{3}} \right) + {\epsilon \left( {q_{0} + {iq}_{1} + {jq}_{2} + {kq}_{3}} \right)}}} \\{= {p_{0} + {ip}_{1} + {jp}_{2} + {kp}_{3} + {\epsilon \; q_{0}} + {\epsilon \; {iq}_{1}} + {\epsilon \; {jq}_{2}} + {\epsilon \; {kq}_{3}}}}\end{matrix} & (16)\end{matrix}$

Both p and q are quaternions. It is defined that another biquaternionB=p′±ϵq′, and the product of the two biquaternions is shown in formula(17):

AB=(p+ϵq)(p′+ϵq′)=(pp′+qq′)+ϵ(pq′+qp′)  (17)

where the quaternion product theory of the quaternions p, q, p′, and q′is not described herein.

Biquaternion property 2: conjugate of the biquaternion;

conjugate of the biquaternion A may be defined as Ac, as shown informula (18):

$\begin{matrix}\begin{matrix}{A_{c} = {p_{c} + {\epsilon \; q_{c}}}} \\{= {\left( {p_{0} - {i\; p_{1}} - {j\; p_{2}} - {k\; p_{3}}} \right) + {\epsilon \left( {q_{0} - {i\; q_{1}} - {j\; q_{2}} - {k\; q_{3}}} \right)}}} \\{= {p_{0} - {i\; p_{1}} - {j\; p_{2}} - {k\; p_{3}} + {\epsilon \; q_{0}} - {\epsilon \; i\; q_{1}} - {\epsilon \; j\; q_{2}} - {\epsilon \; k\; q_{3}}}}\end{matrix} & (18)\end{matrix}$

p_(c) is conjugate of quaternion p.

In order to calculate the modulus value |ψ_(cas)(x, y, z)| of thehypercomplex signal, formulas (16) to (19) need to be first used tocalculate the product of ψ_(cas)(x, y, z) and the conjugate thereof,that is, ψ_(cas)(ψ_(cas))_(c), as shown in formula (19):

$\begin{matrix}{{{\psi_{cas}\left( \phi_{cas} \right)}_{c} = {{\frac{a_{1}^{2} + a_{3}^{2} + a_{5}^{2} + a_{7}^{2}}{4} + {i(0)} + {j(0)} + {k(0)} + {\epsilon \frac{{a_{1}a_{3}{\sin \left( {\phi_{1} - \phi_{3}} \right)}} - {a_{5}a_{7}{\sin \left( {\phi_{5} - \phi_{7}} \right)}}}{2}} + {\epsilon \; {i(0)}} + {\epsilon \; {j(0)}} + {\epsilon \; {k(0)}}} = {\frac{a_{1}^{2} + a_{3}^{2} + a_{5}^{2} + a_{7}^{2}}{4} + {\epsilon \frac{{a_{1}a_{3}{\sin \left( {\phi_{1} - \phi_{3}} \right)}} - {a_{5}a_{7}{\sin \left( {\phi_{5} - \phi_{7}} \right)}}}{2}}}}},} & (19)\end{matrix}$

It can be seen from formula (19) that, a result of ψ_(cas)(ψ_(cas))_(c)only includes two parts, where one part is a real part, that is,

$\frac{a_{1}^{2} + a_{3}^{2} + a_{5}^{2} + a_{7}^{2}}{4},$

the other part is a part that takes c as an imaginary unit, that is,

${\epsilon \frac{{a_{1}a_{3}{\sin \left( {\phi_{1} - \phi_{3}} \right)}} - {a_{5}a_{7}{\sin \left( {\phi_{5} - \phi_{7}} \right)}}}{2}},$

and actually, the part is referred to as a “pseudo real” part of abiquaternion. Other imaginary parts are all 0. The result is greatlyhelpful in calculating the modulus value |ψ_(cas)(x, y, z)|. Thefollowing describes a process of calculating the modulus value|ψ_(cas)(x, y, z)|.

First, a polar coordinate form of a hypercomplex signal ψ_(cas)(x, y,z):

ψ_(cas)=|ψ_(cas)|^(eϵϕa),

|ψ_(cas)| is a modulus value, a is a unit biquaternion (that has aproperty: a product of conjugate and itself is 1, namely, a(a_(c))=1),and ϕ is an angle of the biquaternion. As shown in formula (20):

ψ_(cas)(ψ_(cas))_(c)=|ψ_(cas)|² e^(2ϵϕ)=|ψ_(cas)|²[ch(2ϕ)+ϵsh(2ϕ)],  (20)

ch( ) and sh( ) are a hyperbolic cosine function and a hyperbolic sinefunction respectively. The specific derivation process of the formula isshown as follows:

$\begin{matrix}{e^{2\; \epsilon \; \varphi} = {1 + {2\epsilon \; \varphi} + \frac{\left( {2\; \epsilon \; \varphi} \right)^{2}}{2!} + \frac{\left( {2\; \epsilon \; \varphi} \right)^{3}}{3!} + \ldots + {{\frac{\left( {2\; \epsilon \; \varphi} \right)^{2r}}{\left( {2r} \right)!}++}\frac{\left( {2\; \epsilon \; \varphi} \right)^{{2r} + 1}}{\left( {{2r} + 1} \right)!}} + \ldots}} \\{= {\left\lbrack {1 + \frac{\left( {2\; \epsilon \; \varphi} \right)^{2}}{2!} + \frac{\left( {2\; \epsilon \; \varphi} \right)^{4}}{4!} + \ldots + \frac{\left( {2\; \epsilon \; \varphi} \right)^{2r}}{\left( {2r} \right)!} + \ldots} \right\rbrack +}} \\{\left\lbrack {{2\epsilon \; \varphi} + \frac{\left( {2\; \epsilon \; \varphi} \right)^{3}}{3!} + \frac{\left( {2\; \epsilon \; \varphi} \right)^{5}}{5!} + \ldots + \frac{\left( {2\; \epsilon \; \varphi} \right)^{{2r} + 1}}{\left( {{2r} + 1} \right)!} + \ldots} \right\rbrack} \\{= {\left\lbrack {1 + \frac{\left( {2\; \epsilon \; \varphi} \right)^{2}}{2!} + \frac{\left( {2\; \epsilon \; \varphi} \right)^{4}}{4!} + \ldots + \frac{\left( {2\; \epsilon \; \varphi} \right)^{2r}}{\left( {2r} \right)!} + \ldots} \right\rbrack +}} \\{{\epsilon \left\lbrack {{2\; \varphi} + \frac{\left( {2\; \varphi} \right)^{3}}{3!} + \frac{\left( {2\; \varphi} \right)^{5}}{5!} + \ldots + \frac{\left( {2\; \varphi} \right)^{{2r} + 1}}{\left( {{2r} + 1} \right)!} + \ldots} \right\rbrack}} \\{{= {{{ch}\left( {2\; \varphi} \right)} + {\epsilon \; {{sh}\left( {2\; \varphi} \right)}}}},}\end{matrix}$

where r represents a positive complex number.

In order to simplify the calculation, two symbols M and N may be used torepresent formula (20):

ψ_(cas)(ψ_(cas))_(c) =M+ϵN

M represents real parts in formula (19) and formula (20), and Nrepresents “pseudo real” parts in formula (19) and formula (20). Thefollowing may be obtained:

M ² −N ²=|ψ_(cas)|⁴[ch(2ϕ)² −sh(2ϕ)²]=|ψ_(cas)|⁴

Therefore, |ψ_(cas)|=(M²−N²)^(1/4), and by substituting symbols M and Ninto a content of formula (19), formula (21) may be obtained:

$\begin{matrix}{{{\psi_{cas}} = \sqrt[4]{\left\lbrack \frac{a_{1}^{2} + a_{3}^{2} + a_{5}^{2} + a_{7}^{2}}{4} \right\rbrack^{2} - \left\lbrack \frac{\begin{matrix}{{a_{1}a_{3}{\sin \left( {\phi_{1} - \phi_{3}} \right)}} -} \\{a_{5}a_{7}{\sin \left( {\phi_{5} - \phi_{7}} \right)}}\end{matrix}}{2} \right\rbrack^{2}}},} & (21)\end{matrix}$

A result of formula (21) is the modulus value |ψ_(cas)(x, y, z)| of thefirst hypercomplex signal. Elements representing the modulus value comefrom calculations of formula (8) to formula (11). The calculations arecalculation processes that can be implemented in engineering. Inputinformation is modulus values α₁(x, y, z), α₃(x, y, z), α₅(x, y, z), andα₇(x, y, z) and angles φ₁(x, y, z), φ₃(x, y, z), φ₅(x, y, z), and φ₇(x,y, z) of polar coordinates of formula (8) to formula (11). Output is themodulus value of the first hypercomplex signal, that is, an envelopesignal |ψ_(cas)(x, y, z)|.

That is to say, in this embodiment of this application, the modulusvalue of the first hypercomplex signal may be acquired according to theformula (21).

|ψ_(cas)| represents the modulus value of the first hypercomplex signal,α₁ is a modulus value of a first analytic signal, φ_(i) is an angle ofthe first analytic signal, the first analytic signal is an analyticsignal that is in the first orthant of 8 orthants in a 3D frequencydomain and that corresponds to the input signal, α₃ is a modulus valueof a third analytic signal, φ₃ is an angle of the third analytic signal,the third analytic signal is an analytic signal that is in the thirdorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₅ is a modulus value of a fifthanalytic signal, φ₅ is an angle of the fifth analytic signal, the fifthanalytic signal is an analytic signal that is in the fifth orthant ofthe 8 orthants in the 3D frequency domain and that corresponds to theinput signal, α₇ is a modulus value of a seventh analytic signal, φ₇ isan angle of the seventh analytic signal, the seventh analytic signal isan analytic signal that is in the seventh orthant of the 8 orthants inthe 3D frequency domain and that corresponds to the input signal, andthe plurality of analytic signals include the first analytic signal, thethird analytic signal, the fifth analytic signal, and the seventhanalytic signal.

After acquiring the modulus value of the first hypercomplex signal shownin formula (21), the envelope information used for indicating theto-be-detected object in the 3D ultrasound image may be obtained. Inthis embodiment of this application, the 3D ultrasound image may begenerated according to the envelope information. A process of generatingthe 3D ultrasound image according to the envelope information is notspecifically limited herein, and may specifically include, but is notlimited to, image processing means such as denoising.

In the technical solution provided in step S206, after generating the 3Dultrasound image, the 3D ultrasound image may be displayed on a displaydevice and/or the envelope information in the 3D ultrasound image isdisplayed on the display device. The display device and the detectiondevice may form an integral structure, or the display device and thedetection device may be separate components. When the display device andthe detection device are independent of each other, after the detectiondevice generates the 3D ultrasound image, the 3D ultrasound image may besent to the display device for displaying, so that a user may observethe to-be-detected object from the display device clearly andintuitively.

Using the ultrasound image display method in this embodiment of thisapplication, because the envelope information used for indicating theto-be-detected object in the 3D ultrasound image is obtained byperforming a modulus calculation on the 3D RF signal, but not obtainedby splicing the one-dimensional envelope information, the brightness anddefinition of the to-be-detected object indicated by the envelopeinformation in the 3D ultrasound image are greater than the brightnessand definition of the to-be-detected object in a one-dimensionalultrasound image or a two-dimensional ultrasound image. Therefore, thisembodiment of this application may make the to-be-detected object bemore clearly displayed in the 3D ultrasound image, thereby improving theaccuracy of the 3D ultrasound image.

The ultrasound image display method provided in this application may beused to direct 3D envelope detection of the B-mode ultrasound image. Inthis application, based on a form of 3D convolution and a form ofClifford algebra biquaternion, an analytic signal of high-dimensionalhypercomplex numbers is defined to calculate the 3D amplitude of the 3DRF signal at a time, that is, the 3D ultrasound image of the 3D RFsignal. The Hilbert transform is used to implement an engineeringimplementation method for the provided hypercomplex signal and itsmodulus value. Compared with a conventional method for reconstructing aB-mode ultrasound image by splicing one-dimensional envelope signals ofone-dimensional ultrasound RF signals according to spatial positions,this application completely abandons the method for obtaining a B-modeultrasound image by splicing one-dimensional envelope signals, to avoida reconstruction error of the 3D B-mode ultrasound image that is formedby splicing the one-dimensional envelope signals. In addition, thisapplication is further applicable to one-time envelope detection of atwo-dimensional B-mode ultrasound image and a 3D B-mode ultrasoundimage.

This application may be applied to a device that performs an envelopecalculation on the 3D RF signal, for example, applied to B-mode imagingof a 3D ultrasound device. As shown in FIG. 3, in the 3D B-mode imageacquired by using a 3D fan-shaped probe, the method may implementone-time imaging on the 3D data.

This application may implement the modulus calculation on a 3D RFultrasound signal, to acquire a 3D envelope image thereof (that is, theimage indicated by the envelope information in the foregoing embodimentof this application). The modulus value of the 3D RF ultrasound signalherein refers to the 3D envelope image. On the basis of the 3D envelopeimage, 3D ultrasound image may be obtained by using any two-dimensionalor 3D image post-processing algorithm.

As shown in FIG. 5, a platform where a 3D fan-shaped ultrasound probe510 is used to acquire a 3D RF signal is described by using an example.A phantom 530 is under the 3D fan-shaped ultrasound probe to imitate ahuman body. A biopsy needle 520 is inserted into the phantom 530 toimitate an experiment of inserting the biopsy needle into the human bodyto acquire human tissue for a subsequent biopsy. In a process ofacquiring the human tissue by the biopsy needle, a doctor uses theultrasound probe to observe a location of the biopsy needle in the humanbody, aiming to make a needle of the probe reach a predetermined tissuelocation.

FIG. 6 is marked with 3 terms of coordinate axis directions used in the3D ultrasound: axial 602, lateral 604, and elevation 606. FIG. 6 alsoshows a ultrasound probe 610 and a biopsy needle 620. In FIG. 6, the xaxis and the y axis of the 3D RF signal form a slice. The z axis is anelevation axis that represents a different two-dimensional slice. Theultrasound envelope image of the 3D RF signal acquired in FIG. 6 iscalculated separately by using the existing methods and the methodprovided in this application. FIG. 7 shows a part of the result, whichis a result of slice 15 in FIG. 6. The location of the biopsy needle ison the slice. Charts 710 and 720 are results calculated by using theexisting one-dimensional method and two-dimensional method. Chart 730 isa result calculated by using the method for this application. In chart730, a white area that is highlighted, diagonal, long and thin is thelocation of the biopsy needle. The higher brightness indicates that thebiopsy needle is more apparently displayed on the ultrasound envelopeimage. In order to compare details, chart 740 acquires profiles in avertical direction of the image. Chart 750 is profiles along thedirection of the probe. Higher values of the profiles indicate that thebrightness is higher, that is, the probe is more clearly displayed onthe envelope image. It can be seen from the values of the profiles that,the brightness in the 3D method provided in this application in thelocation of the probe is mostly higher than those in the one-dimensionalmethod and/or the two-dimensional method.

FIG. 8 is enlarged chart 730. In FIG. 8, a diagonal quadrangular box isthe location of the biopsy needle. Two imaginary lines are locations ofthe profiles in chart 740 and chart 750.

FIG. 9 is enlarged chart 740. FIG. 10 is enlarged chart 750. The middleof two horizontal lines in FIG. 9 is the location of the biopsy needle.The foregoing examples are two results based on the 3D RF data of thefan-shaped ultrasound probe.

In order to prove the universality of this application, the followingexample is a calculation of the 3D envelope image based on the 3D RFdata of the linear probe. A similar conclusion may also be drawn: the 3Denvelope image of the solution can better display location informationof the needle.

FIG. 11 is a schematic diagram of a linear ultrasound probe 1110. FIG.11 also shows a biopsy needle 1120 and a phantom 1130. FIG. 12 is acoordinate axis example of data acquired by the linear ultrasound probe1210, and the data is in a cubic structure including a plurality ofslices, for example, slice 1, slice 16, and slice 29. FIG. 13 is aresult of a 3D envelope of the linear ultrasound probe. Chart 1310 is aresult of the one-dimensional method, chart 1320 is a result of thetwo-dimensional method, and chart 1330 is a result of the method of thisapplication. FIG. 14 is a brightness comparison of pixels of theprofiles in a vertical direction in the quadrangle. The middle of twohorizontal lines is the location of the biopsy needle. The brightness ofthe result of the 3D method is the highest. The needle is displayed mostapparently. FIG. 15 is a brightness comparison of pixels of the profilesalong the direction of the needle in the quadrangle. The whole curve isthe location of the biopsy needle in the image. The brightness of theresult of the 3D method is the highest, and the needle is displayed mostapparently.

The solution of this application may solve every envelope calculation ofthe 3D high-frequency signal mathematically. At an application level,the solution may also solve the problem that the 3D signal is ahigh-frequency signal in one dimension or two dimensions but not ahigh-frequency signal in other dimensions. Therefore, the solution canbe potentially applied to various physics and engineering applicationproblems related to a modulus value calculation of 3D high-frequencysignals, such as, high-frequency signal communications, high-frequencyradar signal demodulation, encryption of images by using high-frequencyinformation, and decryption requiring a calculation of envelopeinformation of signals.

To make the description simple, the foregoing method embodiments arestated as a series of action combinations. However, a person skilled inthe art needs to know that this application is not limited on thedescribed sequence of the actions because according to this application,certain steps may use another sequence or may be simultaneouslyperformed. In addition, it is to be understood by a person skilled inthe art that the embodiments described in the specification all belongto exemplary embodiments and the actions and modules are not mandatoryto this application.

According to the foregoing descriptions of implementations, a personskilled in the art may clearly learn that the method according to theforegoing embodiments may be implemented by using software and anecessary general hardware platform, or certainly may be implemented byusing hardware. However, in most cases, the former is a betterimplementation. Based on such an understanding, the technical solutionsin this application essentially or the part contributing on the relatedart may be implemented in the form of a software product. The computersoftware product is stored in a storage medium (such as a read-onlymemory (ROM)/random access memory (RAM), a magnetic disk, or an opticaldisc), and includes several instructions for instructing a terminaldevice (which may be a mobile phone, a computer, a server, a networkdevice, and the like) to perform the method described in the embodimentsof this application.

According to another aspect of the embodiments of this application, anultrasound image display apparatus for implementing the ultrasound imagedisplay method is further provided. FIG. 16 is a schematic diagram of anoptional ultrasound image display apparatus according to an embodimentof this application. As shown in FIG. 16, the apparatus may include:

an acquiring unit 22, configured to acquire an input signal obtained byperforming detection on a to-be-detected object by a detection device,the input signal being a 3D RF signal; a calculating unit 24, configuredto perform a modulus calculation on the 3D RF signal to obtain envelopeinformation in a 3D ultrasound image, the modulus calculation being atleast used for directly acquiring a 3D amplitude of the 3D RF signal;and a display unit 26, configured to display the envelope information inthe 3D ultrasound image on a display device, the envelope informationbeing used for indicating the to-be-detected object.

The acquiring unit 22 in this embodiment may be configured to performstep S202 in the embodiments of this application, the calculating unit24 in this embodiment may be configured to perform step S204 in theembodiments of this application, and the display unit 26 in thisembodiment may be configured to perform step S206 in the embodiments ofthis application.

Implemented examples and application scenarios of the foregoing modulesare the same as those of the corresponding steps, but are not limited tothe content disclosed in the foregoing embodiments. The foregoingmodules may be run in the hardware environment shown in FIG. 1 as a partof the apparatus, and may be implemented by software, or may beimplemented by hardware.

Optionally, the calculating unit 24 may include: a first acquiringmodule, configured to acquire a first hypercomplex signal correspondingto the 3D RF signal, the first hypercomplex signal being a sum of 8components, and each component being represented by modulus values andangles of a plurality of analytic signals corresponding to the inputsignal; and a second acquiring module, configured to acquire a modulusvalue of the first hypercomplex signal, the modulus value of the firsthypercomplex signal being used for representing the 3D amplitude of the3D RF signal, and envelope information including the modulus value ofthe first hypercomplex signal.

Optionally, the first acquiring module may include: a first acquiringsubmodule, configured to acquire a second hypercomplex signalcorresponding to the 3D RF signal, the second hypercomplex signalincluding 8 components, and each component being represented by theHilbert transform of the input signal; a second acquiring submodule,configured to acquire a correspondence between the componentsrepresented by the Hilbert transform and the modulus values and anglesof the plurality of analytic signals; and a transforming module,configured to transform the second hypercomplex signal into the firsthypercomplex signal according to the correspondence.

Optionally, the second acquiring module is configured to acquire themodulus value of the first hypercomplex signal according to thefollowing formula:

${\psi_{cas}} = \sqrt[4]{\left\lbrack \frac{a_{1}^{2} + a_{3}^{2} + a_{5}^{2} + a_{7}^{2}}{4} \right\rbrack^{2} - \left\lbrack \frac{\begin{matrix}{{a_{1}a_{3}{\sin \left( {\phi_{1} - \phi_{3}} \right)}} -} \\{a_{5}a_{7}{\sin \left( {\phi_{5} - \phi_{7}} \right)}}\end{matrix}}{2} \right\rbrack^{2}}$

|ψ_(cas)| represents the modulus value of the first hypercomplex signal,α₁ is a modulus value of a first analytic signal, φ₁ is an angle of thefirst analytic signal, the first analytic signal is an analytic signalthat is in the first orthant of 8 orthants in a 3D frequency domain andthat corresponds to the input signal, α₃ is a modulus value of a thirdanalytic signal, φ₃ is an angle of the third analytic signal, the thirdanalytic signal is an analytic signal that is in the third orthant ofthe 8 orthants in the 3D frequency domain and that corresponds to theinput signal, α₅ is a modulus value of a fifth analytic signal, φ₅ is anangle of the fifth analytic signal, the fifth analytic signal is ananalytic signal that is in the fifth orthant of the 8 orthants in the 3Dfrequency domain and that corresponds to the input signal, α₇ is amodulus value of a seventh analytic signal, φ₇ is an angle of theseventh analytic signal, the seventh analytic signal is an analyticsignal that is in the seventh orthant of the 8 orthants in the 3Dfrequency domain and that corresponds to the input signal, and theplurality of analytic signals include the first analytic signal, thethird analytic signal, the fifth analytic signal, and the seventhanalytic signal.

Optionally, the brightness of the to-be-detected object indicated by theenvelope information in the 3D ultrasound image is greater than thebrightness of the to-be-detected object in a one-dimensional ultrasoundimage or a two-dimensional ultrasound image.

Implemented examples and application scenarios of the foregoing modulesare the same as those of the corresponding steps, but are not limited tothe content disclosed in the foregoing embodiments. The foregoingmodules may be run in the hardware environment shown in FIG. 1 as a partof the apparatus, and may be implemented by software, or may beimplemented by hardware.

Through the foregoing modules, the to-be-detected object is accuratelydisplayed in the 3D ultrasound image, to achieve a technical effect ofimproving the accuracy of the 3D ultrasound image, thereby solving thetechnical problem that the 3D B-mode ultrasound image reconstructed inthe related art has a reconstruction error that reduces the accuracy ofthe 3D B-mode ultrasound image.

According to still another aspect of the embodiments of thisapplication, an electronic device for implementing the ultrasound imagedisplay method is further provided.

FIG. 17 is a structural block diagram of an electronic device accordingto an embodiment of this application. As shown in FIG. 17, theelectronic device may include: one or more (only one processor is shownin the figure) processors 201 and a memory 203, the memory 203 storing acomputer program, and the processor 201 being configured to run thecomputer program to perform the ultrasound image display methodaccording to the embodiments of this application.

The memory 203 may be configured to store a computer program and amodule, for example, a program instruction/module corresponding to theultrasound image display method and apparatus in the embodiments of thisapplication, and the processor 201 performs various functionalapplications and data processing by running the computer program and themodule stored in the memory 203, that is, implementing the foregoingultrasound image display method. The memory 203 may include a high-speedrandom access memory, and may further include a non-volatile memory, forexample, one or more magnetic storage apparatuses, flash memories, orother non-volatile solid-state memories. In some embodiments, the memory203 may further include memories that are remotely disposed relative tothe processor 201, and the remote memories may be connected to aterminal via a network. Examples of the network include, but are notlimited to, the Internet, an intranet, a local area network, a mobilecommunications network, and a combination thereof.

Optionally, as shown in FIG. 17, the electronic device may furtherinclude: a transmission apparatus 205 and an input/output device 207.The transmission apparatus 205 is configured to receive or send datathrough a network. Specific instances of the foregoing network mayinclude a wired network and a wireless network. In an example, thetransmission apparatus 205 includes a network interface controller(NIC), and the network interface controller may be connected to anothernetwork device or a router by using a network cable, so as tocommunicate with the Internet or a local area network. In an example,the transmission apparatus 205 is a radio frequency (RF) module, and theradio frequency module is configured to communicate with the Internet ina wireless manner.

A person of ordinary skill in the art may understand that, the structureshown in FIG. 17 is only schematic. The electronic device may be aterminal device such as a smartphone (such as an Android mobile phone oran iOS mobile phone), a tablet computer, a palmtop computer, a mobileInternet device (MID), or a PAD. FIG. 17 does not constitute alimitation on a structure of the foregoing electronic device. Forexample, the electronic device may further include more or fewercomponents (for example, a network interface and a display apparatus)than those shown in FIG. 17, or has a configuration different from thatshown in FIG. 17.

Optionally, in this embodiment, the memory 203 may be configured tostore the computer program.

Optionally, in this embodiment, the processor is configured to run thecomputer program for performing the following steps: acquiring an inputsignal obtained by performing detection on a to-be-detected object by adetection device, the input signal being a 3D RF signal; performing amodulus calculation on the 3D RF signal to obtain envelope informationin a 3D ultrasound image, the modulus calculation being at least usedfor directly acquiring a 3D amplitude of the 3D RF signal; anddisplaying the envelope information in the 3D ultrasound image on thedisplay device, the envelope information being used for indicating theto-be-detected object.

The processor 201 is further configured to perform the following steps:acquiring a first hypercomplex signal corresponding to the 3D RF signal,the first hypercomplex signal being a sum of 8 components, and eachcomponent being represented by modulus values and angles of a pluralityof analytic signals corresponding to the input signal; and acquiring amodulus value of the first hypercomplex signal, the modulus value of thefirst hypercomplex signal being used for representing the 3D amplitudeof the 3D RF signal, and envelope information including the modulusvalue of the first hypercomplex signal.

The processor 201 is further configured to perform the following steps:acquiring a second hypercomplex signal corresponding to the 3D RFsignal, the second hypercomplex signal including 8 components, and eachcomponent being represented by the Hilbert transform of the inputsignal; acquiring a correspondence between the components represented bythe Hilbert transform and the modulus values and angles of the pluralityof analytic signals; and transforming the second hypercomplex signalinto the first hypercomplex signal according to the correspondence.

The processor 201 is further configured to perform the following step:acquiring the modulus value of the first hypercomplex signal accordingto the following formula:

${\psi_{cas}} = \sqrt[4]{\left\lbrack \frac{a_{1}^{2} + a_{3}^{2} + a_{5}^{2} + a_{7}^{2}}{4} \right\rbrack^{2} - \left\lbrack \frac{\begin{matrix}{{a_{1}a_{3}{\sin \left( {\phi_{1} - \phi_{3}} \right)}} -} \\{a_{5}a_{7}{\sin \left( {\phi_{5} - \phi_{7}} \right)}}\end{matrix}}{2} \right\rbrack^{2}}$

|ψ_(cas)| represents the modulus value of the first hypercomplex signal,α₁ is a modulus value of a first analytic signal, φ₁ is an angle of thefirst analytic signal, the first analytic signal is an analytic signalthat is in the first orthant of 8 orthants in a 3D frequency domain andthat corresponds to the input signal, α₃ is a modulus value of a thirdanalytic signal, φ₃ is an angle of the third analytic signal, the thirdanalytic signal is an analytic signal that is in the third orthant ofthe 8 orthants in the 3D frequency domain and that corresponds to theinput signal, α₅ is a modulus value of a fifth analytic signal, φ₅ is anangle of the fifth analytic signal, the fifth analytic signal is ananalytic signal that is in the fifth orthant of the 8 orthants in the 3Dfrequency domain and that corresponds to the input signal, α₇ is amodulus value of a seventh analytic signal, φ₇ is an angle of theseventh analytic signal, the seventh analytic signal is an analyticsignal that is in the seventh orthant of the 8 orthants in the 3Dfrequency domain and that corresponds to the input signal, and theplurality of analytic signals include the first analytic signal, thethird analytic signal, the fifth analytic signal, and the seventhanalytic signal.

Optionally, for a specific example in this embodiment, reference may bemade to the example described in the foregoing embodiment, and detailsare not described herein again in this embodiment.

By using this embodiment of this application, an ultrasound imagedisplay solution is provided. By acquiring the input signal obtained byperforming the detection on the to-be-detected object by the detectiondevice, the input signal being the 3D RF signal; performing the moduluscalculation on the 3D RF signal to obtain the envelope information inthe 3D ultrasound image, the modulus calculation being at least used fordirectly acquiring the 3D amplitude of the 3D RF signal; and displayingthe envelope information in the 3D ultrasound image on the displaydevice, the envelope information being used for indicating theto-be-detected object, the to-be-detected object is accurately displayedin the 3D ultrasound image, to achieve a technical effect of improvingthe accuracy of the 3D ultrasound image, thereby solving the technicalproblem that the 3D B-mode ultrasound image reconstructed in the relatedart has a reconstruction error that reduces the accuracy of the 3DB-mode ultrasound image.

According to still another aspect of the embodiments of thisapplication, a storage medium is further provided. The storage mediumstores a computer program, the computer program being configured toperform a step of an ultrasound image display method in the foregoingembodiment when being run.

Optionally, in this embodiment, the storage medium may be located in atleast one network device of a plurality of network devices in a networkshown in the foregoing embodiments.

Optionally, in this embodiment, the storage medium is configured tostore the computer program for performing the following steps:

S1. Acquire an input signal obtained by performing detection on ato-be-detected object by a detection device, the input signal being a 3DRF signal.

S2. Perform a modulus calculation on the 3D RF signal to obtain envelopeinformation in a 3D ultrasound image, the modulus calculation being atleast used for directly acquiring a 3D amplitude of the 3D RF signal.

S3. Display the envelope information in the 3D ultrasound image on adisplay device, the envelope information being used for indicating theto-be-detected object.

Optionally, the storage medium is further configured to store thecomputer program for performing the following steps: acquiring a firsthypercomplex signal corresponding to the 3D RF signal, the firsthypercomplex signal being a sum of 8 components, and each componentbeing represented by modulus values and angles of a plurality ofanalytic signals corresponding to the input signal; and acquiring amodulus value of the first hypercomplex signal, the modulus value of thefirst hypercomplex signal being used for representing the 3D amplitudeof the 3D RF signal, and envelope information including the modulusvalue of the first hypercomplex signal.

Optionally, the storage medium is further configured to store thecomputer program for performing the following steps: acquiring a secondhypercomplex signal corresponding to the 3D RF signal, the secondhypercomplex signal including 8 components, and each component beingrepresented by the Hilbert transform of the input signal; acquiring acorrespondence between the components represented by the Hilberttransform and the modulus values and angles of the plurality of analyticsignals; and transforming the second hypercomplex signal into the firsthypercomplex signal according to the correspondence.

Optionally, the storage medium is further configured to store thecomputer program for performing the following step: acquiring themodulus value of the first hypercomplex signal according to thefollowing formula:

${\psi_{cas}} = \sqrt[4]{\left\lbrack \frac{a_{1}^{2} + a_{3}^{2} + a_{5}^{2} + a_{7}^{2}}{4} \right\rbrack^{2} - \left\lbrack \frac{\begin{matrix}{{a_{1}a_{3}{\sin \left( {\phi_{1} - \phi_{3}} \right)}} -} \\{a_{5}a_{7}{\sin \left( {\phi_{5} - \phi_{7}} \right)}}\end{matrix}}{2} \right\rbrack^{2}}$

|ψ_(cas)| represents the modulus value of the first hypercomplex signal,α₁ is a modulus value of a first analytic signal, φ_(i) is an angle ofthe first analytic signal, the first analytic signal is an analyticsignal that is in the first orthant of 8 orthants in a 3D frequencydomain and that corresponds to the input signal, α₃ is a modulus valueof a third analytic signal, φ₃ is an angle of the third analytic signal,the third analytic signal is an analytic signal that is in the thirdorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₅ is a modulus value of a fifthanalytic signal, φ₅ is an angle of the fifth analytic signal, the fifthanalytic signal is an analytic signal that is in the fifth orthant ofthe 8 orthants in the 3D frequency domain and that corresponds to theinput signal, α₇ is a modulus value of a seventh analytic signal, φ₇ isan angle of the seventh analytic signal, the seventh analytic signal isan analytic signal that is in the seventh orthant of the 8 orthants inthe 3D frequency domain and that corresponds to the input signal, andthe plurality of analytic signals include the first analytic signal, thethird analytic signal, the fifth analytic signal, and the seventhanalytic signal.

Optionally, for a specific example in this embodiment, reference may bemade to the example described in the foregoing embodiment, and detailsare not described herein again in this embodiment.

Optionally, in this embodiment, a person of ordinary skill in the artmay understand that all or some of the steps of the methods in theforegoing embodiments may be implemented by a program instructingrelevant hardware of the terminal device. The program may be stored in acomputer-readable storage medium. The storage medium may include a flashdisk, a read-only memory (ROM), a random access memory (RAM), a magneticdisk, an optical disc, and the like.

The sequence numbers of the foregoing embodiments of this applicationare merely for the convenience of description, and do not imply thepreference among the embodiments.

When the integrated unit in the foregoing embodiments is implemented inthe form of a software functional unit and sold or used as anindependent product, the integrated unit may be stored in the foregoingcomputer-readable storage medium. Based on such an understanding, thetechnical solution of this application essentially, or a partcontributing to the related art, or all or a part of the technicalsolution may be implemented in a form of a software product. Thecomputer software product is stored in a storage medium and includesseveral instructions for instructing one or more computer devices (whichmay be a personal computer, a server, a network device, or the like) toperform all or some of steps of the methods in the embodiments of thisapplication.

In the foregoing embodiments of this application, descriptions of theembodiments have different emphases. As for parts that are not describedin detail in one embodiment, reference can be made to the relevantdescriptions of the other embodiments.

In the several embodiments provided in this application, it isunderstood that the disclosed client may be implemented in othermanners. The described apparatus embodiment is merely an example. Forexample, the unit division is merely logical function division and maybe another division in an actual implementation. For example, aplurality of units or components may be combined or integrated intoanother system, or some features may be ignored or not performed. Inaddition, the displayed or discussed mutual couplings or directcouplings or communication connections may be implemented by using someinterfaces. The indirect couplings or communication connections betweenunits or modules may be implemented in electric or other forms.

The units described as separate parts may or may not be physicallyseparate. Parts displayed as units may or may not be physical units, andmay be located in one position, or may be distributed on a plurality ofnetwork units. Some or all of the units may be selected according toactual requirements to achieve the objectives of the solutions in theembodiments.

In addition, functional units in the embodiments of this application maybe integrated into one processing unit, or each of the units may existalone physically, or two or more units are integrated into one unit. Theintegrated unit may be implemented in the form of hardware, or may beimplemented in the form of a software function unit.

The foregoing descriptions are merely exemplary implementations of thisapplication. A person of ordinary skill in the art may further makeseveral improvements and refinements without departing from theprinciple of this application, and the improvements and refinementsshall fall within the protection scope of this application.

1. A method for displaying an ultrasound image, the method comprising:acquiring, by a device comprising a memory storing instructions and aprocessor in communication with the memory, an input signal byperforming detection on a to-be-detected object, the input signalcomprising a three-dimensional (3D) radio-frequency (RF) signal;performing, by the device, a modulus calculation on the 3D RF signal toobtain envelope information in a 3D ultrasound image, the moduluscalculation being at least used for directly acquiring a 3D amplitude ofthe 3D RF signal; and displaying, by the device, the envelopeinformation in the 3D ultrasound image, the envelope information beingat least used for indicating the to-be-detected object.
 2. The methodaccording to claim 1, wherein the performing the modulus calculation onthe 3D RF signal to obtain the envelope information in the 3D ultrasoundimage comprises: acquiring, by the device, a first hypercomplex signalcorresponding to the 3D RF signal, the first hypercomplex signal being asum of 8 components, and each component being represented by modulusvalues and angles of a plurality of analytic signals corresponding tothe input signal; and acquiring, by the device, the envelope informationcomprising a modulus value of the first hypercomplex signal, the modulusvalue of the first hypercomplex signal being used for representing the3D amplitude of the 3D RF signal.
 3. The method according to claim 2,wherein the acquiring the first hypercomplex signal corresponding to the3D RF signal comprises: acquiring, by the device, a second hypercomplexsignal corresponding to the 3D RF signal, the second hypercomplex signalcomprising 8 components, and each component being represented by aHilbert transform of the input signal; acquiring, by the device, acorrespondence between the components represented by the HilbertTransform and the modulus values and angles of the plurality of analyticsignals; and transforming, by the device, the second hypercomplex signalinto the first hypercomplex signal according to the correspondence. 4.The method according to claim 3, wherein: the second hypercomplex signalcomprises the following:ψ_(cas)(x, y, z) = f + i H_(yz){f} + j(−H_(xz){f}) + k H_(xy){f} + ϵ(−H{f}) + ϵ iH_(x){f} + ϵ jH_(y){f} + ϵ kH_(z){f},wherein f represents the 3D RF signal f(x, y, z), H_(z){f} represents aHilbert transform of the 3D RF signal f(x, y, z) in the z direction,H_(y){f} represents a Hilbert transform of the 3D RF signal f(x, y, z)in the y direction, H_(x){f} represents a Hilbert transform of the 3D RFsignal f(x, y, z) in the x direction, H_(yz){f} represents a Hilberttransform of the 3D RF signal f(x, y, z) in the y direction and the zdirection, H_(xz){f} represents a Hilbert transform of the 3D RF signalf(x, y, z) in the x direction and the z direction, and H_(xy){f}represents a Hilbert transform of the 3D RF signal f(x, y, z) in the xdirection and the y direction.
 5. The method according to claim 4,wherein: the correspondence between the components represented by theHilbert Transform and the modulus values and angles of the plurality ofanalytic signals comprises the following:f=¼(α₁ cos φ₁+α₃ cos φ₃+α₅ cos φ₅+α₇ cos φ₇),H _(yz) {f}=¼(−α₁ cos φ₁+α₃ cos φ₃+α₅ cos φ₅−α₇ cos φ₇),−H _(xz) {f}=¼(α₁ cos φ₁+α₃ cos φ₃−α₅ cos φ₅−α₇ cos φ₇),H _(xy) {f}=¼(−α₁ cos φ₁+α₃ cos φ₃−α₅ cos φ₅+α₇ cos φ₇),−H{f}=¼(α₁ sin φ₁−α₃ sin φ₃−α₅ sin φ₅+α₇ sin φ₇),H _(x) {f}=¼(α₁ sin φ₁+α₃ sin φ₃+α₅ sin φ₅+α₇ sin φ₇),H _(y) {f}=¼(α₁ sin φ₁−α₃ sin φ₃+α₅ sin φ₅−α₇ sin φ₇),H _(z) {f}=¼(α₁ sin φ₁+α₃ sin φ₃−α₅ sin φ₅−α₇ sin φ₇),  (14) α₁ being amodulus value of a first analytic signal, φ_(i) being an angle of thefirst analytic signal, the first analytic signal being an analyticsignal that is in the first orthant of 8 orthants in a 3D frequencydomain and that corresponds to the input signal, α₃ being a modulusvalue of a third analytic signal, φ₃ being an angle of the thirdanalytic signal, the third analytic signal being an analytic signal thatis in the third orthant of the 8 orthants in the 3D frequency domain andthat corresponds to the input signal, α₅ being a modulus value of afifth analytic signal, φ₅ being an angle of the fifth analytic signal,the fifth analytic signal being an analytic signal that is in the fifthorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₇ being a modulus value of a seventhanalytic signal, φ₇ being an angle of the seventh analytic signal, andthe seventh analytic signal being an analytic signal that is in theseventh orthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal.
 6. The method according to claim 2,further comprising: acquiring, by the device, the modulus value of thefirst hypercomplex signal according to the following:${{\psi_{cas}} = \sqrt[4]{\left\lbrack \frac{a_{1}^{2} + a_{3}^{2} + a_{5}^{2} + a_{7}^{2}}{4} \right\rbrack^{2} - \left\lbrack \frac{\begin{matrix}{{a_{1}a_{3}{\sin \left( {\phi_{1} - \phi_{3}} \right)}} -} \\{a_{5}a_{7}{\sin \left( {\phi_{5} - \phi_{7}} \right)}}\end{matrix}}{2} \right\rbrack^{2}}},$ |ψ_(cas)| representing themodulus value of the first hypercomplex signal, α₁ being a modulus valueof a first analytic signal, φ_(i) being an angle of the first analyticsignal, the first analytic signal being an analytic signal that is inthe first orthant of 8 orthants in a 3D frequency domain and thatcorresponds to the input signal, α₃ being a modulus value of a thirdanalytic signal, φ₃ being an angle of the third analytic signal, thethird analytic signal being an analytic signal that is in the thirdorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₅ being a modulus value of a fifthanalytic signal, φ₅ being an angle of the fifth analytic signal, thefifth analytic signal being an analytic signal that is in the fifthorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₇ being a modulus value of a seventhanalytic signal, φ₇ being an angle of the seventh analytic signal, theseventh analytic signal being an analytic signal that is in the seventhorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, and the plurality of analytic signalscomprising the first analytic signal, the third analytic signal, thefifth analytic signal, and the seventh analytic signal.
 7. The methodaccording to claim 1, wherein: a brightness of the to-be-detected objectindicated by the envelope information in the 3D ultrasound image isgreater than a brightness of the to-be-detected object in aone-dimensional ultrasound image or a two-dimensional ultrasound image.8. An apparatus for displaying an ultrasound image, the apparatuscomprising: a memory storing instructions; and a processor incommunication with the memory, wherein, when the processor executes theinstructions, the processor is configured to cause the apparatus to:acquire an input signal by performing detection on a to-be-detectedobject, the input signal comprising a three-dimensional (3D)radio-frequency (RF) signal, perform a modulus calculation on the 3D RFsignal to obtain envelope information in a 3D ultrasound image, themodulus calculation being at least used for directly acquiring a 3Damplitude of the 3D RF signal, and display the envelope information inthe 3D ultrasound image, the envelope information being at least usedfor indicating the to-be-detected object.
 9. The apparatus according toclaim 8, wherein, when the processor is configured to cause theapparatus to perform the modulus calculation on the 3D RF signal toobtain the envelope information in the 3D ultrasound image, theprocessor is configured to cause the apparatus to: acquire a firsthypercomplex signal corresponding to the 3D RF signal, the firsthypercomplex signal being a sum of 8 components, and each componentbeing represented by modulus values and angles of a plurality ofanalytic signals corresponding to the input signal; and acquire theenvelope information comprising a modulus value of the firsthypercomplex signal, the modulus value of the first hypercomplex signalbeing used for representing the 3D amplitude of the 3D RF signal. 10.The apparatus according to claim 9, wherein, when the processor isconfigured to cause the apparatus to acquire the first hypercomplexsignal corresponding to the 3D RF signal, the processor is configured tocause the apparatus to: acquire a second hypercomplex signalcorresponding to the 3D RF signal, the second hypercomplex signalcomprising 8 components, and each component being represented by aHilbert transform of the input signal; acquire a correspondence betweenthe components represented by the Hilbert Transform and the modulusvalues and angles of the plurality of analytic signals; and transformthe second hypercomplex signal into the first hypercomplex signalaccording to the correspondence.
 11. The apparatus according to claim10, wherein: the second hypercomplex signal comprises the following:ψ_(cas)(x, y, z) = f + i H_(yz){f} + j(−H_(xz){f}) + k H_(xy){f} + ϵ(−H{f}) + ϵ iH_(x){f} + ϵ jH_(y){f} + ϵ kH_(z){f},wherein f represents the 3D RF signal f(x, y, z), H_(z){f} represents aHilbert transform of the 3D RF signal f(x, y, z) in the z direction,H_(y){f} represents a Hilbert transform of the 3D RF signal f(x, y, z)in the y direction, H_(x){f} represents a Hilbert transform of the 3D RFsignal f(x, y, z) in the x direction, H_(yz){f} represents a Hilberttransform of the 3D RF signal f(x, y, z) in the y direction and the zdirection, H_(xz){f} represents a Hilbert transform of the 3D RF signalf(x, y, z) in the x direction and the z direction, and H_(xy){f}represents a Hilbert transform of the 3D RF signal f(x, y, z) in the xdirection and the y direction.
 12. The apparatus according to claim 11,wherein: the correspondence between the components represented by theHilbert Transform and the modulus values and angles of the plurality ofanalytic signals comprises the following:f=¼(α₁ cos φ₁+α₃ cos φ₃+α₅ cos φ₅+α₇ cos φ₇),H _(yz) {f}=¼(−α₁ cos φ₁+α₃ cos φ₃+α₅ cos φ₅−α₇ cos φ₇),−H _(xz) {f}=¼(α₁ cos φ₁+α₃ cos φ₃−α₅ cos φ₅−α₇ cos φ₇),H _(xy) {f}=¼(−α₁ cos φ₁+α₃ cos φ₃−α₅ cos φ₅+α₇ cos φ₇),−H{f}=¼(α₁ sin φ₁−α₃ sin φ₃−α₅ sin φ₅+α₇ sin φ₇),H _(x) {f}=¼(α₁ sin φ₁+α₃ sin φ₃+α₅ sin φ₅+α₇ sin φ₇),H _(y) {f}=¼(α₁ sin φ₁−α₃ sin φ₃+α₅ sin φ₅−α₇ sin φ₇),H _(z) {f}=¼(α₁ sin φ₁+α₃ sin φ₃−α₅ sin φ₅−α₇ sin φ₇),  (14) α₁ being amodulus value of a first analytic signal, φ₁ being an angle of the firstanalytic signal, the first analytic signal being an analytic signal thatis in the first orthant of 8 orthants in a 3D frequency domain and thatcorresponds to the input signal, α₃ being a modulus value of a thirdanalytic signal, φ₃ being an angle of the third analytic signal, thethird analytic signal being an analytic signal that is in the thirdorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₅ being a modulus value of a fifthanalytic signal, φ₅ being an angle of the fifth analytic signal, thefifth analytic signal being an analytic signal that is in the fifthorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₇ being a modulus value of a seventhanalytic signal, φ₇ being an angle of the seventh analytic signal, andthe seventh analytic signal being an analytic signal that is in theseventh orthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal.
 13. The apparatus according to claim 9,wherein, when the processor executes the instructions, the processor isconfigured to further cause the apparatus to: acquire the modulus valueof the first hypercomplex signal according to the following:${{\psi_{cas}} = \sqrt[4]{\left\lbrack \frac{a_{1}^{2} + a_{3}^{2} + a_{5}^{2} + a_{7}^{2}}{4} \right\rbrack^{2} - \left\lbrack \frac{\begin{matrix}{{a_{1}a_{3}{\sin \left( {\phi_{1} - \phi_{3}} \right)}} -} \\{a_{5}a_{7}{\sin \left( {\phi_{5} - \phi_{7}} \right)}}\end{matrix}}{2} \right\rbrack^{2}}},$ |ψ_(cas)| representing themodulus value of the first hypercomplex signal, α₁ being a modulus valueof a first analytic signal, φ₁ being an angle of the first analyticsignal, the first analytic signal being an analytic signal that is inthe first orthant of 8 orthants in a 3D frequency domain and thatcorresponds to the input signal, α₃ being a modulus value of a thirdanalytic signal, φ₃ being an angle of the third analytic signal, thethird analytic signal being an analytic signal that is in the thirdorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₅ being a modulus value of a fifthanalytic signal, φ₅ being an angle of the fifth analytic signal, thefifth analytic signal being an analytic signal that is in the fifthorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₇ being a modulus value of a seventhanalytic signal, φ₇ being an angle of the seventh analytic signal, theseventh analytic signal being an analytic signal that is in the seventhorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, and the plurality of analytic signalscomprising the first analytic signal, the third analytic signal, thefifth analytic signal, and the seventh analytic signal.
 14. Theapparatus according to claim 8, wherein: a brightness of theto-be-detected object indicated by the envelope information in the 3Dultrasound image is greater than a brightness of the to-be-detectedobject in a one-dimensional ultrasound image or a two-dimensionalultrasound image.
 15. A non-transitory computer readable storage mediumstoring computer readable instructions, wherein, the computer readableinstructions, when executed by a processor, are configured to cause theprocessor to perform: acquiring an input signal by performing detectionon a to-be-detected object, the input signal comprising athree-dimensional (3D) radio-frequency (RF) signal; performing a moduluscalculation on the 3D RF signal to obtain envelope information in a 3Dultrasound image, the modulus calculation being at least used fordirectly acquiring a 3D amplitude of the 3D RF signal; and displayingthe envelope information in the 3D ultrasound image, the envelopeinformation being at least used for indicating the to-be-detectedobject.
 16. The non-transitory computer readable storage mediumaccording to claim 15, wherein, when the computer readable instructionsare configured to cause the processor to perform performing the moduluscalculation on the 3D RF signal to obtain the envelope information inthe 3D ultrasound image, the computer readable instructions areconfigured to cause the processor to perform: acquiring a firsthypercomplex signal corresponding to the 3D RF signal, the firsthypercomplex signal being a sum of 8 components, and each componentbeing represented by modulus values and angles of a plurality ofanalytic signals corresponding to the input signal; and acquiring theenvelope information comprising a modulus value of the firsthypercomplex signal, the modulus value of the first hypercomplex signalbeing used for representing the 3D amplitude of the 3D RF signal. 17.The non-transitory computer readable storage medium according to claim16, wherein, when the computer readable instructions are configured tocause the processor to perform acquiring the first hypercomplex signalcorresponding to the 3D RF signal, the computer readable instructionsare configured to cause the processor to perform: acquiring a secondhypercomplex signal corresponding to the 3D RF signal, the secondhypercomplex signal comprising 8 components, and each component beingrepresented by a Hilbert transform of the input signal; acquiring acorrespondence between the components represented by the HilbertTransform and the modulus values and angles of the plurality of analyticsignals; and transforming the second hypercomplex signal into the firsthypercomplex signal according to the correspondence.
 18. Thenon-transitory computer readable storage medium according to claim 17,wherein: the second hypercomplex signal comprises the following:ψ_(cas)(x, y, z) = f + i H_(yz){f} + j(−H_(xz){f}) + k H_(xy){f} + ϵ(−H{f}) + ϵ iH_(x){f} + ϵ jH_(y){f} + ϵ kH_(z){f},wherein f represents the 3D RF signal f(x, y, z), H_(z){f} represents aHilbert transform of the 3D RF signal f(x, y, z) in the z direction,H_(y){f} represents a Hilbert transform of the 3D RF signal f(x, y, z)in the y direction, H_(x){f} represents a Hilbert transform of the 3D RFsignal f(x, y, z) in the x direction, H_(yz){f} represents a Hilberttransform of the 3D RF signal f(x, y, z) in the y direction and the zdirection, Hail represents a Hilbert transform of the 3D RF signal f(x,y, z) in the x direction and the z direction, and Hall represents aHilbert transform of the 3D RF signal f(x, y, z) in the x direction andthe y direction.
 19. The non-transitory computer readable storage mediumaccording to claim 18, wherein: the correspondence between thecomponents represented by the Hilbert Transform and the modulus valuesand angles of the plurality of analytic signals comprises the following:f=¼(α₁ cos φ₁+α₃ cos φ₃+α₅ cos φ₅+α₇ cos φ₇),H _(yz) {f}=¼(−α₁ cos φ₁+α₃ cos φ₃+α₅ cos φ₅−α₇ cos φ₇),−H _(xz) {f}=¼(α₁ cos φ₁+α₃ cos φ₃−α₅ cos φ₅−α₇ cos φ₇),H _(xy) {f}=¼(−α₁ cos φ₁+α₃ cos φ₃−α₅ cos φ₅+α₇ cos φ₇),−H{f}=¼(α₁ sin φ₁−α₃ sin φ₃−α₅ sin φ₅+α₇ sin φ₇),H _(x) {f}=¼(α₁ sin φ₁+α₃ sin φ₃+α₅ sin φ₅+α₇ sin φ₇),H _(y) {f}=¼(α₁ sin φ₁−α₃ sin φ₃+α₅ sin φ₅−α₇ sin φ₇),H _(z) {f}=¼(α₁ sin φ₁+α₃ sin φ₃−α₅ sin φ₅−α₇ sin φ₇),  (14) α₁ being amodulus value of a first analytic signal, φ₁ being an angle of the firstanalytic signal, the first analytic signal being an analytic signal thatis in the first orthant of 8 orthants in a 3D frequency domain and thatcorresponds to the input signal, α₃ being a modulus value of a thirdanalytic signal, φ₃ being an angle of the third analytic signal, thethird analytic signal being an analytic signal that is in the thirdorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₅ being a modulus value of a fifthanalytic signal, φ₅ being an angle of the fifth analytic signal, thefifth analytic signal being an analytic signal that is in the fifthorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₇ being a modulus value of a seventhanalytic signal, φ₇ being an angle of the seventh analytic signal, andthe seventh analytic signal being an analytic signal that is in theseventh orthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal.
 20. The non-transitory computerreadable storage medium according to claim 16, wherein, the computerreadable instructions, when executed by a processor, are configured tofurther cause the processor to perform: acquiring the modulus value ofthe first hypercomplex signal according to the following:${{\psi_{cas}} = \sqrt[4]{\left\lbrack \frac{a_{1}^{2} + a_{3}^{2} + a_{5}^{2} + a_{7}^{2}}{4} \right\rbrack^{2} - \left\lbrack \frac{\begin{matrix}{{a_{1}a_{3}{\sin \left( {\phi_{1} - \phi_{3}} \right)}} -} \\{a_{5}a_{7}{\sin \left( {\phi_{5} - \phi_{7}} \right)}}\end{matrix}}{2} \right\rbrack^{2}}},$ |ψ_(cas)| representing themodulus value of the first hypercomplex signal, α₁ being a modulus valueof a first analytic signal, φ₁ being an angle of the first analyticsignal, the first analytic signal being an analytic signal that is inthe first orthant of 8 orthants in a 3D frequency domain and thatcorresponds to the input signal, α₃ being a modulus value of a thirdanalytic signal, φ₃ being an angle of the third analytic signal, thethird analytic signal being an analytic signal that is in the thirdorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₅ being a modulus value of a fifthanalytic signal, φ₅ being an angle of the fifth analytic signal, thefifth analytic signal being an analytic signal that is in the fifthorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, α₇ being a modulus value of a seventhanalytic signal, φ₇ being an angle of the seventh analytic signal, theseventh analytic signal being an analytic signal that is in the seventhorthant of the 8 orthants in the 3D frequency domain and thatcorresponds to the input signal, and the plurality of analytic signalscomprising the first analytic signal, the third analytic signal, thefifth analytic signal, and the seventh analytic signal.